One of the American dreams is home ownership. However, according to the Mortgage Guaranty Insurance Company, “[r]elative to the growth in home prices over the last century, Americans are earning less and, as a result, saving less.” As a result, the down payment required to secure a mortgage often prevents young individuals just “starting out” from buying a home. Consequently, home mortgages having low down payments have become very popular. The less money a borrower has invested in a home, however, the greater the risk of default. Therefore, while there is some risk that a borrower may default with a conventional mortgage which typically requires a twenty percent (20%) down payment, this risk is increased for borrowers who are only putting down five percent (5%) or ten percent (10%). Low down payment mortgages, therefore, often require that the borrower obtain some type of mortgage insurance to protect the lender against loss if the borrower defaults on the mortgage. However, even with such protection, the lender typically is not able to recoup the entire amount of the mortgage.
Lenders and mortgage insurers try to minimize their exposure by obtaining information on borrowers indicative of their risk of defaulting on a mortgage, such as through credit reports or mortgage service systems such as The Mortgage Office, MORESERV and TRAKKER. There are also several existing consumer and mortgage scoring systems which generate underwriting scores to assist mortgage insurers in this regard, such as for example, the Fair Issac Consumer (FICO) score, the Private Mortgage Insurance (PMI) aura score, the United Guaranty ACUscore, and the ARCS subprime mortgage score.
None of these scoring tools, however, assess risk attributable to fraud (i.e., data integrity). For example, a lender may manipulate the loan information to qualify an otherwise unqualified borrower, or a borrower may falsify income or employment information in order to obtain the loan. To the extent fraudulent claims are not detected, the costs associated with paying them are ultimately borne by the consumer. According to a Sep. 26, 2001 article in Realty Times, reports of possible fraudulent activity in connection with a mortgage increased fifty-seven percent (57%) in the first quarter of this year.
Fraud can originate from numerous sources, such as lenders, borrowers, appraisers, title agents, real estate agents and builders. Fraud can be injected into the loan process in a number of ways, such as through the use of false credit histories, false income/employment information, falsified appraisals, inflated property values and false identification. For example, loan officers might fabricate pay stubs to help a borrower qualify for a loan that the borrower might not otherwise qualify for so that he or she can collect a commission. Likewise, a borrower might submit falsified tax returns to ensure he or she qualifies for the loan.
The potential for fraud increases as the number of parties involved in the transaction increases. Increases in mortgage fraud are also due to a number of other factors, such as (1) the creation of new and creative forms of financing, coupled with automated underwriting, (2) the increased availability of personal information via the Internet, and (3) the low-cost of computer equipment such as printers and copiers that produce high quality copies such that one can fabricate authentic-looking documents (i.e., pay stubs, tax returns).
Not only do fraudulent loans result in enormous financial losses, misrepresenting information on a loan application is illegal. Moreover, penalties for fraudulent lending violations include substantial monetary penalties such as repayment of twice the amount of all interest, fees, discounts and charges as well as court and attorney fees to the borrower. In addition, such violations can result in the temporary or permanent suspension of business privileges of the lender, such as the ability to sell to quasi-governmental agencies (e.g., Freddie Mac and Fannie Mae) or in secondary markets, or the ability to sell certain types of loans. In some cases, lenders can lose their licenses and face imprisonment. In the secondary market, purchasers and assignees can be held liable for all claims on loans in their possession. These costs are then often passed on to consumers in the form of higher loan costs, higher lending fees and higher interest rates.
Yet another risk associated with funding or insuring a loan relates to the accuracy of the valuation of the subject property. One of the most common problems associated with property valuations is known as property flipping. This practice involves a property that is bought and then resold (i.e., flipped) several times, each time at a falsely inflated price. The property is then sold to an unsuspecting mortgage company that pays much more for the property than its market value that can result in a substantial loss to the mortgage lender upon the reselling of the property. Typically, lenders use internal or third party property valuation models or tools such as Appintell, Inc.'s ValVerify, Case Shiller Weiss' CASA, Solimar's Basis100 or First American's product suite which includes Value Point, Home Price Index, Assessed Value Model, AREA's, and Value Point Plus to analyze the value of the property provided in the loan documents and score it based on its accuracy. Such an analysis looks at factors like the value of other properties around the location of the subject property and the selling prices of comparable properties. This score is usually in the form of a value or grade representing a confidence level, which corresponds to a range of predicated value. For example, in the case of CASA, Grade A refers to a predicted value range within 6%, Grade B refers to a predicted value range between 6% and 8%, Grade C refers to a predicted value range of between 8% and 10%, Grade D refers to a predicted value range between 10% and 14%, and Grade E refers to a predicted value range between 14% and 20%. The bigger the discrepancy between the property value provided in the loan documents and the property value determined by such models or tools, the greater the risk in funding or insuring the loan.
Currently, fraud, underwriting and property valuation scoring systems originate from different sources. As a result, they are not compatible with each other. In other words, mortgage service providers must go to one company to have a risk assessment of the loan from an underwriting perspective, a different company to have a risk assessment of the loan from a fraud perspective, and possibly yet a different company to have a risk assessment of the loan from a property valuation perspective. This cumbersome process not only significantly delays the underwriting process, but also increases its costs tremendously. In fact, the single largest insurance policy acquisition cost in mortgage insurance is contract underwriting. Approximately half of loan public filings by private mortgage insurers in 2000 were referred to underwriters for manual review after the loan was scored vis-à-vis the borrower's credit history. Moreover, since the scores are not compatible, they cannot be combined into an overall score reflecting the level of risk of funding or insuring a loan based on at least two of the three scores. The potential cost and time savings as well as value of an automatic risk assessment system that takes into account risk from at least two of a fraud, underwriting and property valuation perspective all provided from one source is enormous.
There is, therefore, a need for an automated system and method that assesses the risk associated with funding or insuring a loan based on a plurality of risk factors.